Key Responsibilities
Project and Team Leadership
Collaborate with business stakeholders and domain experts to understand data requirements and translate them into clear conceptual, logical, and physical data models.
Work closely with data engineers, analytics teams, and AI/ML practitioners to ensure data models are aligned with downstream consumption needs.
Aptitude to work independently on modeling workstreams within client engagements, including requirements gathering, design, and documentation.
Document & communicate modeling decisions, trade-offs, and best practices to both technical and non-technical audiences.
Contribute to project delivery through high-quality, low-defect delivery”, documentation, design reviews, and model governance activities.
Data Modelling & Semantic Modelling Expertise
Design and maintain conceptual, logical, and physical data models for structured and semi-structured data across enterprise systems.
Develop reusable, extensible data models supporting analytics, reporting, AI/ML feature engineering, and decision science use cases.
Apply semantic modeling techniques, including domain modeling, entity relationships, hierarchies, and taxonomies.
Enable ontology and knowledge graph modeling, translating subject-matter knowledge into machine-readable representations.
Ensure alignment of data models with enterprise architecture principles, data standards, and best practices.
AI & GenAI Enablement
Design data and semantic models that act as foundational datasets for AI/ML and Generative AI systems.
Enable explainability, reasoning, and contextual grounding through ontology-driven approaches and graph-based data models.
Partner with data science and AI teams to ensure models support feature reuse, RAG pipelines, and intelligent agent workflows.
Contribute to data model designs that improve trust, interpretability, and scalability of AI-driven solutions.
Data Governance & Standards
Follow and contribute to data modeling standards, naming conventions, and design guidelines across projects.
Support data governance initiatives including metadata management, lineage, and documentation.
Ensure consistency, quality, and reusability of data assets across platforms and use cases.
Business Impact and Innovation
Translate complex business concepts into clear, well-structured data models that accelerate analytics and AI adoption.
Enable faster solution development by providing high-quality, well-documented data foundations.
Support measurable outcomes by improving data usability, consistency, and decision-making effectiveness.
Required Qualifications
Experience
4–6 years of experience with 3+ years of hands-on experience in data modelling, information modelling, or data architecture roles.
Experience designing conceptual, logical, and physical data models.
Experience working in consulting or client-facing roles is highly preferred.
Education
Bachelor’s or Master’s degree in Computer Science, Data Science, Information Systems, Engineering, or a related field.
Job Title - Decision Science Practitioner Consultant
Management Level: Consultant
Location: Bangalore/ Kolkata/Gurugram/Hyderabad
Must have skills: Data Modelling, Conceptual & Logical Design, Semantic Modelling and Understanding of Knowledge Graphs
Good to have skills: Data Science, Ontologies, AI/ML Data Enablement, GenAI Foundations
Key Responsibilities
Project and Team Leadership
Collaborate with business stakeholders and domain experts to understand data requirements and translate them into clear conceptual, logical, and physical data models.
Work closely with data engineers, analytics teams, and AI/ML practitioners to ensure data models are aligned with downstream consumption needs.
Aptitude to work independently on modeling workstreams within client engagements, including requirements gathering, design, and documentation.
Document & communicate modeling decisions, trade-offs, and best practices to both technical and non-technical audiences.
Contribute to project delivery through high-quality, low-defect delivery”, documentation, design reviews, and model governance activities.